Initial commit - 611 cybersecurity skills across all subdomains

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mukul975
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# Standards - False Positive Reduction in SIEM
## Detection Quality Metrics (Industry Standards)
| Metric | Excellent | Good | Needs Improvement | Critical |
|---|---|---|---|---|
| False Positive Rate | < 10% | 10-20% | 20-40% | > 40% |
| Rule Precision | > 0.90 | 0.80-0.90 | 0.60-0.80 | < 0.60 |
| Mean Triage Time | < 5 min | 5-10 min | 10-20 min | > 20 min |
| Alert-to-Incident Ratio | 1:5 | 1:10 | 1:20 | > 1:50 |
## Tuning Frameworks
### NIST Continuous Monitoring (SP 800-137)
- Requires regular assessment and adjustment of detection capabilities
- Defines metrics-based approach to monitoring effectiveness
### SANS Detection Maturity Model
- Level 1: Basic alerts with high FP rate
- Level 2: Tuned alerts with correlation
- Level 3: Behavioral analytics reducing noise
- Level 4: Automated tuning with ML feedback loops
## Allowlist Management Standards
- All exclusions require documented justification
- Expiry dates mandatory (90-day maximum default)
- Quarterly review of all active exclusions
- Approval from detection engineering lead required
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# Workflows - False Positive Reduction
## Tuning Cycle
```
Identify Noisy Rules --> Analyze FP Root Causes --> Tune Rules -->
Validate with Testing --> Measure Improvement --> Report --> Repeat
```
## FP Analysis Categorization
| Category | Action | Example |
|---|---|---|
| Known benign | Add to allowlist | Vulnerability scanner IPs |
| Threshold too low | Raise threshold | Login failure count from 5 to 20 |
| Missing context | Add correlation | PowerShell + network = suspicious |
| Missing enrichment | Add lookup | Asset criticality context |
| Rule outdated | Rewrite or retire | Legacy detection no longer relevant |